Papers Panoptic Segmentation
“Panoptic Segmentation” 태그가 달린 논문 505편 · 필터 해제
GhostPoint: Self-Supervised Representation Learning by Hallucinating Occluded LiDAR Structure
3D object detection from LiDAR point clouds is a core problem in autonomous driving. Recent advances in self-supervised learning (SSL) enable scalable pretraining and transfers well to per-point tasks such as semantic an…
Self-Supervised LearningRepresentation LearningPanoptic Segmentation3D Object DetectionExtending a Large View Synthesis Model for Multi-view Panoptic Segmentation
Large view synthesis models synthesize novel views through cross-view attention without explicit 3D representations, and recent studies have shown that they learn accurate spatial correspondence from RGB supervision alon…
Panoptic SegmentationNovel View SynthesisScene Understanding3D ReconstructionInstance-Enriched Semantic Maps for Visual Language Navigation
Visual Language Navigation (VLN) aims to enable an embodied agent to navigate complex environments by following natural language instructions. Recent approaches build semantic spatial maps and leverage Large Language Mod…
Panoptic SegmentationDecision MakingDM-KG: A Novel Method for Boosting Spatial Cognition of Vision-Language Models in Street View Imagery
As vision-language models (VLMs) are increasingly deployed in geospatial question answering and visual scene understanding, improving their spatial cognition capability on street view imagery for complex logical reasonin…
Visual Question AnsweringPanoptic SegmentationScene UnderstandingSpatial ReasoningPano3D: Unified 3D Reconstruction and Panoptic Segmentation
Recent advances in 3D feedforward reconstruction neural networks have achieved remarkable success in dense reconstruction from images without any camera parameters. Yet, equipping these models with robust semantic unders…
Panoptic Segmentation3D ReconstructionEPS3D: End-to-End Feed-Forward 3D Panoptic Segmentation
This paper introduces EPS3D, a new end-to-end feed-forward framework for open-vocabulary 3D panoptic segmentation. Unlike existing methods relying on additional preprocessing, we design an end-to-end architecture, with a…
Panoptic SegmentationScene Understanding3D scene EditingPrAda: Few-Shot Visual Adaptation for Text-Prompted Segmentation
Segmenting images is critical for visual understanding but demands extensive pixel-level annotations. Foundational models have enabled new paradigms for predicting new classes guided by textual prompts, without annotatio…
Panoptic SegmentationImage ClassificationU-SEG: Uncertainty in SEGmentation -- A systematic multi-variable exploration
In this study, we explore in depth a few under-studied topics at the intersection of uncertainty estimation and segmentation. Prior work has shown that the quality of uncertainty estimates can be very sensitive to a rang…
Panoptic SegmentationFuTCR: Future-Targeted Contrast and Repulsion for Continual Panoptic Segmentation
Continual Panoptic Segmentation (CPS) requires methods that can quickly adapt to new categories over time. The nature of this dense prediction task means that training images may contain a mix of labeled and unlabeled ob…
Panoptic SegmentationMambaPanoptic: A Vision Mamba-based Structured State Space Framework for Panoptic Segmentation
Panoptic segmentation requires the simultaneous recognition of countable thing instances and amorphous stuff regions, placing joint demands on long-range context modelling, multi-scale feature representation, and efficie…
Panoptic SegmentationHyp2Former: Hierarchy-Aware Hyperbolic Embeddings for Open-Set Panoptic Segmentation
Recognizing unknown objects is crucial for safety-critical applications such as autonomous driving and robotics. Open-Set Panoptic Segmentation (OPS) aims to segment known thing and stuff classes while identifying valid …
Panoptic SegmentationAutonomous DrivingPanDA: Unsupervised Domain Adaptation for Multimodal 3D Panoptic Segmentation in Autonomous Driving
This paper presents the first study on Unsupervised Domain Adaptation (UDA) for multimodal 3D panoptic segmentation (mm-3DPS), aiming to improve generalization under domain shifts commonly encountered in real-world auton…
Unsupervised Domain Adaptation3D Semantic SegmentationRepresentation LearningPanoptic SegmentationAdverse-to-the-eXtreme Panoptic Segmentation: URVIS 2026 Study and Benchmark
This paper presents the report of the URVIS 2026 challenge on adverse-to-extreme panoptic segmentation. As the first challenge of its kind, it attracted 17 registered participants and 47 submissions, with 4 teams reachin…
Panoptic SegmentationΨ-Map: Panoptic Surface Integrated Mapping Enables Real2Sim Transfer
Open-vocabulary panoptic reconstruction is essential for advanced robotics perception and simulation. However, existing methods based on 3D Gaussian Splatting (3DGS) often struggle to simultaneously achieve geometric acc…
Panoptic SegmentationKuramoto Oscillatory Phase Encoding: Neuro-inspired Synchronization for Improved Learning Efficiency
Spatiotemporal neural dynamics and oscillatory synchronization are widely implicated in biological information processing and have been hypothesized to support flexible coordination such as feature binding. By contrast, …
Panoptic SegmentationVisual ReasoningLiPS: Lightweight Panoptic Segmentation for Resource-Constrained Robotics
Panoptic segmentation is a key enabler for robotic perception, as it unifies semantic understanding with object-level reasoning. However, the increasing complexity of state-of-the-art models makes them unsuitable for dep…
Panoptic SegmentationTowards Foundation Models for 3D Scene Understanding: Instance-Aware Self-Supervised Learning for Point Clouds
Recent advances in self-supervised learning (SSL) for point clouds have substantially improved 3D scene understanding without human annotations. Existing approaches emphasize semantic awareness by enforcing feature consi…
Self-Supervised LearningPanoptic SegmentationInstance SegmentationScene UnderstandingMitigating Objectness Bias and Region-to-Text Misalignment for Open-Vocabulary Panoptic Segmentation
Open-vocabulary panoptic segmentation remains hindered by two coupled issues: (i) mask selection bias, where objectness heads trained on closed vocabularies suppress masks of categories not observed in training, and (ii)…
Panoptic SegmentationImage ClassificationPanORama: Multiview Consistent Panoptic Segmentation in Operating Rooms
Operating rooms (ORs) are cluttered, dynamic, highly occluded environments, where reliable spatial understanding is essential for situational awareness during complex surgical workflows. Achieving spatial understanding f…
Panoptic SegmentationEfficient RGB-D Scene Understanding via Multi-task Adaptive Learning and Cross-dimensional Feature Guidance
Scene understanding plays a critical role in enabling intelligence and autonomy in robotic systems. Traditional approaches often face challenges, including occlusions, ambiguous boundaries, and the inability to adapt att…
Panoptic SegmentationSemantic SegmentationInstance SegmentationScene Classification